New inexpensive and efficient catalyst materials for energy transformations are necessary for future sustainable energy solutions. Theoretical heterogeneous catalysis based on atomistic simulations provides a fast way to screen materials and predict their relative performance. In an originally data-poor field, current increases in computing power will soon enable us to compare millions of results. As such, the ability to be efficient in handling large amounts of data will become key to productivity and new discoveries. We are developing a software infrastructure to enable us to do that. We are working towards integrating workflows and results, which will let the computational scientists spend less time running calculations and managing data and more time on scientific analysis and developing ideas.